Fuzzy and Multiple Regression Modelling for Evaluation of Intact Rock Strength Based on Point Load, Schmidt Hammer and Sonic Velocity

Summary.Uniaxial Compressive Strength (UCS), considered to be one of the most useful rock properties for mining and civil engineering applications, has been estimated from some index test results by fuzzy and multiple regression modelling. Laboratory investigations including Uniaxial Compressive Strength (UCS), Point Load Index test (PL), Schmidt Hammer Hardness test (SHR) and Sonic velocity (Vp) test have been carried out on nine different rock types yielding to 305 tested specimens in total. Average values along with the standard deviations (Stdev) as well as Coefficients of variation (CoV) have been calculated for each rock type. Having constructed the Mamdani Fuzzy algorithm, UCS of intact rock samples was then predicted using a data driven fuzzy model. The predicted values derived from fuzzy model were compared with multi-linear statistical model. Comparison proved that the best model predictions have been achieved by fuzzy modelling in contrast to multi-linear statistical modelling. As a result, the developed fuzzy model based on point load, Schmidt hammer and sonic velocity can be used as a tool to predict UCS of intact rocks.

[1]  Lotfi A. Zadeh,et al.  Fuzzy Sets , 1996, Inf. Control..

[2]  J. A. Franklin,et al.  THE POINT-LOAD STRENGTH TEST , 1972 .

[3]  Z. T. Bieniawski,et al.  Suggested methods for determining the uniaxial compressive strength and deformability of rock materials: Part 1. Suggested method for determination of the uniaxial compressive strength of rock materials , 1979 .

[4]  E. T. Brown.  Rock characterization, testing & monitoring: ISRM suggested methods , 1981 .

[5]  E. Broch,et al.  ESTIMATION OF STRENGTH ANISOTROPY USING THE POINT LOAD TEST , 1983 .

[6]  Luis E. Vallejo,et al.  Correlation Between Unconfined Compressive And Point Load Strengths For Appalachian Rocks , 1989 .

[7]  Hans Hellendoorn,et al.  Defuzzification in Fuzzy Controllers , 1993, J. Intell. Fuzzy Syst..

[8]  V. Singh,et al.  Correlation between point load index and compressive strength for quartzite rocks , 1993 .

[9]  T. Ross.  Fuzzy Logic with Engineering Applications , 1994 .

[10]  Giovanni Muscato,et al.  Membership function shape and the dynamic behaviour of fuzzy systems , 1994 .

[11]  K. T. Chau,et al.  Uniaxial compressive strength and point load strength of rocks , 1996 .

[12]  Robert Babuska,et al.  Fuzzy Modeling for Control , 1998 .

[13]  Magne Setnes,et al.  Rule-based modeling: precision and transparency , 1998, IEEE Trans. Syst. Man Cybern. Part C.

[14]  Robert Babuška,et al.  Fuzzy model for the prediction of unconfined compressive strength of rock samples , 1999 .

[15]  Paul M. Santi,et al.  Predicting the unconfined compressive strength of the Breathitt shale using slake durability, Shore hardness and rock structural properties , 1999 .

[16]  Oded Katz,et al.  Evaluation of mechanical rock properties using a Schmidt Hammer , 2000 .

[17]  S. Kahraman.  Evaluation of simple methods for assessing the uniaxial compressive strength of rock , 2001 .

[18]  M. Srivastava.  Methods of Multivariate Statistics , 2002 .

[19]  C. Gokceoğlu,et al.  Estimating the deformation modulus of rock masses: a comparative study , 2003 .

[20]  Candan Gokceoglu,et al.  An application of fuzzy sets to the Geological Strength Index (GSI) system used in rock engineering , 2003 .

[21]  Djebbar Tiab,et al.  Point-Load Strength Test , 2004 .

[22]  Candan Gokceoglu,et al.  A fuzzy model to predict the uniaxial compressive strength and the modulus of elasticity of a problematic rock , 2004, Eng. Appl. Artif. Intell..